PROJECT SUMMARY/ABSTRACT Comorbidity is pervasive among the learning disabilities (LDs) (comorbidity rates of 25-50%) and is a key predictor of academic and functional outcomes, yet little is known about the cognitive mechanisms that increase a child?s risk for multiple disorders. This project proposes a multiple deficit model of LDs where shared cognitive risk factors contribute to comorbidity of reading and math (basic and higher-order skills) and ADHD. The overall goal of this project is to use converging methods, including latent modeling, experimental methods, and behavioral genetics, to identify the role of shared cognitive risk factors in the comorbidity of LDs and ADHD. Potential shared cognitive deficits between learning disabilities and ADHD include processing speed (PS), executive functions (EFs), and specific domains of implicit learning. Although these factors have each been examined in LDs individually, this is the first study to assess the impact of these related constructs on comorbidity across LDs. One challenge with the PS construct is the ?task impurity? of the measures. To address this concern, we will systematically examine 4 theoretical models (some non-exclusive) about the role of PS in LDs and ADHD: (1) PS is reducible to cognitive g, (2) PS is reducible to EF, (3) PS is a domain- general factor, (4) PS has content-specific components that are associated with specific academic skills. Aim 1 will examine these 4 models by introducing new experimental PS tasks and leveraging existing data with advanced latent models of the shared and unique variance among the constructs. Another potential shared cognitive risk factor among learning disabilities are deficits in implicit learning, specifically the subdomains of procedural learning and statistical learning, which we have not yet studied in this sample. Aim 1 will include new measures of procedural (motor-based) and statistical (language-based) learning. This will be the first study to examine the association of these constructs with multiple LDs and ADHD. Because this LD center employs a genetically-sensitive twin design, we will be able to draw genetic inferences from the best-fitting cognitive models. In Aim 2, we will determine whether shared cognitive risk factors also share genetic relationships with the comorbid LDs. The population of bilingual youth is growing exponentially in the US, yet we still know very little about academic development in this population. In Aim 3, we plan to test the best-fitting multiple deficit model from Aim 1 in a sample of bilingual, Hispanic youth. This analysis will be an important test of the universality of the multiple deficit model where points of divergence will have important clinical implications. The focus of this project on identifying and dissecting shared cognitive risk factors for LDs and ADHD has clinical relevance for assessment of comorbidity risk and for novel treatment targets that may impact generalized cognitive risk mechanisms.